Numerical study for the design optimization of a two-phase ejector with R134a refrigerant
- Authors
- Baek, Sunghoon; Song, Simon
- Issue Date
- Sep-2018
- Publisher
- KOREAN SOC MECHANICAL ENGINEERS
- Keywords
- Two-phase ejector; Low-pressure refrigeration cycle; Shape optimization; Entrainment performance
- Citation
- JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY, v.32, no.9, pp.4231 - 4236
- Indexed
- SCIE
SCOPUS
KCI
- Journal Title
- JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY
- Volume
- 32
- Number
- 9
- Start Page
- 4231
- End Page
- 4236
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/16105
- DOI
- 10.1007/s12206-018-0821-5
- ISSN
- 1738-494X
- Abstract
- As the use of refrigeration systems continues to increase around the world, the interest in improving energy efficiency of a refrigeration system is also steadily increasing. A two-phase ejector has received attention as an alternative to improve the performance of a vapor-compression refrigeration cycle. Many theoretical and experimental studies have been performed to improve the efficiency of the ejector refrigeration cycle; however, a numerical study using computational fluid dynamics is required owing to the complexity of the flow physics inside the two-phase ejector. Recently, several numerical studies for the two-phase ejector have been conducted. However, these studies primarily focused on the validation of the numerical codes, and few studies have focused on the effects of the design parameters on the performance and shape optimization. Therefore, in this study, the shape of the two-phase ejector was optimized to maximize the entrainment performance utilizing R134a refrigerant. A validated RANS simulation with an evaporation-condensation model was used for analyzing the flow behaviors inside the ejector. In addition, an evolutionary algorithm (EA) and a micro-genetic algorithm (MGA) were used to determine the optimal design point based on an approximate model. The optimized ejector design showed a 55 % higher entrainment performance than that of the baseline model.
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